Skip to main content

Advertisement

SpringerLink
Log in

Application of various cytotoxic endpoints for the toxicity prioritization of fine dust (PM2.5) sources using a multi-criteria decision-making approach

  • Original Paper
  • Published:
Environmental Geochemistry and Health Aims and scope Submit manuscript

Abstract

Fine dust (PM2.5) is generated from various sources, and many studies have reported on the sources of PM2.5. However, the current research on PM2.5 toxicity based on its sources is insufficient. In this study, we developed a framework for the prioritization of fine dust (PM2.5) sources on the basis of the multi-endpoint toxicities using the multi-criteria decision-making method (MCDM). To obtain the multi-endpoint toxicities of PM2.5 sources, cell mortality, reactive oxygen species (ROS), inflammation and mutagenicity were measured for diesel exhaust particles (DEP), gasoline exhaust particles (GEP), rice straw burning particles (RBP), coal combustion particles (CCP) and tunnel dust particles (TDP). The integrative toxicity score (ITS) of the PM2.5 source was calculated using MCDM, which consist of four steps: (1) defining the decision-making matrix, (2) normalization and weighting, (3) calculating the ITS (linear aggregation) and (4) a global sensitivity analysis. The indicator of cell mortality had the highest weight (0.3780) followed by inflammation (0.2471), ROS (0.2178) and mutagenicity (0.1571). Additionally, the ITS based on the sources contributing to PM2.5 resulted in the following order: DEP (0.89), GEP (0.44), RBP (0.40), CCP (0.23) and TDP (0.06). The relative toxicity index (RTI), which represents the ratio of toxicity due to the difference in sources, increases as the contribution of the highly toxic sources increases. The RTI over 1 is closely associated with an increased contribution from highly toxic sources, such as diesel exhaust, gasoline exhaust and biomass burning. It is necessary to investigate the toxicity of various PM2.5 sources and PM2.5 risk based on the sources.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Ahmed, E., Kim, K.-H., Shon, Z.-H., & Song, S.-K. (2015). Long-term trend of airborne particulate matter in Seoul, Korea from 2004 to 2013. Atmospheric Environment,101, 125–133.

    CAS  Google Scholar 

  • Anderson, J. O., Thundiyil, J. G., & Stolbach, A. (2012). Clearing the air: A review of the effects of particulate matter air pollution on human health. Journal of Medical Toxicology,8, 166–175.

    CAS  Google Scholar 

  • Bae, S., Pan, X. C., Kim, S. Y., Park, K., Kim, Y. H., Kim, H., et al. (2010). Exposures to particulate matter and polycyclic aromatic hydrocarbons and oxidative stress in schoolchildren. Environmental Health Perspectives,118, 579–583.

    CAS  Google Scholar 

  • BeruBe, K., Aufderheide, M., Breheny, D., Clothier, R., Combes, R., Duffin, R., et al. (2009). In vitro models of inhalation toxicity and disease. Alternatives to Laboratory Animals,37, 89–141.

    CAS  Google Scholar 

  • Cachon, B. F., Firmin, S., Verdin, A., Ayi-Fanou, L., Billet, S., Cazier, F., et al. (2014). Proinflammatory effects and oxidative stress within human bronchial epithelial cells exposed to atmospheric particulate matter (PM2.5 and PM > 2.5) collected from Cotonou, Benin. Environmental Pollution,185, 340–351.

    CAS  Google Scholar 

  • Cassoni, F., Bocchi, C., Martino, A., Pinto, G., Fontana, F., & Buschini, A. (2004). The Salmonella mutagenicity of urban airborne particulate matter (PM2.5) from eight sites of the Emilia-Romagna regional monitoring network (Italy). Science of the Total Environment,324, 79–90.

    CAS  Google Scholar 

  • Chowdhury, Z., Zheng, M., Schauer, J. J., Sheesley, R. J., Salmon, L. G., Cass, G. R., et al (2007) Speciation of ambient fine organic carbon particles and source apportionment of PM2.5 in Indian cities. Journal of Geophysical Research: Atmospheres, 112, 1–14.

  • Corsini, E., Budello, S., Marabini, L., Galbiati, V., Piazzalunga, A., Barbieri, P., et al. (2013). Comparison of wood smoke PM2.5 obtained from the combustion of FIR and beech pellets on inflammation and DNA damage in A549 and THP-1 human cell lines. Archives of Toxicology,87, 2187–2199.

    CAS  Google Scholar 

  • Dergham, M., Lepers, C., Verdin, A., Cazier, F., Billet, S., Courcot, D., et al. (2015). Temporal–spatial variations of the physicochemical characteristics of air pollution particulate matter (PM 2.5–0.3) and toxicological effects in human bronchial epithelial cells (BEAS-2B). Environmental Research,137, 256–267.

    CAS  Google Scholar 

  • Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining objective weights in multiple criteria problems: The critic method. Computers & Operations Research,22, 763–770.

    Google Scholar 

  • Dumax-Vorzet, A. F., Tate, M., Walmsley, R., Elder, R. H., & Povey, A. C. (2015). Cytotoxicity and genotoxicity of urban particulate matter in mammalian cells. Mutagenesis,30, 621–633.

    CAS  Google Scholar 

  • Gilli, G., Pignata, C., Schilirò, T., Bono, R., La Rosa, A., & Traversi, D. (2007). The mutagenic hazards of environmental PM2.5 in Turin. Environmental Research,103, 168–175.

    CAS  Google Scholar 

  • Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications: A state-of-the-art survey. Berlin: Springer.

    Google Scholar 

  • Jeong, C.-H., Wang, J. M., & Evans, G. J. (2016). Source apportionment of urban particulate matter using hourly resolved trace metals, organics, and inorganic aerosol components. Atmospheric Chemistry and Physics Discussions, 1–32.

  • Jeong J. (1999). Development of evaluation criteria and procedure for the selection of weighting method in multi-criteria decision making. Doctorial thesis, Dongkook University, Seoul.

  • Jo, E.-J., Lee, W.-S., Jo, H.-Y., Kim, C.-H., Eom, J.-S., Mok, J.-H., et al. (2017). Effects of particulate matter on respiratory disease and the impact of meteorological factors in Busan, Korea. Respiratory Medicine,124, 79–87.

    Google Scholar 

  • Kang, C.-M., Kang, B.-W., Sunwoo, Y., & Lee, H. S. (2008). Application of representative PM 2.5 source profiles for the chemical mass balance study in Seoul. Journal of Korean Society for Atmospheric Environment,24, 32–43.

    Google Scholar 

  • Kasurinen, S., Jalava, P. I., Happo, M. S., Sippula, O., Uski, O., Koponen, H., et al. (2017). Particulate emissions from the combustion of birch, beech, and spruce logs cause different cytotoxic responses in A549 cells. Environmental Toxicology,32, 1487–1499.

    CAS  Google Scholar 

  • Kim, Y., & Chung, E.-S. (2014). An index-based robust decision making framework for watershed management in a changing climate. Science of the Total Environment,473, 88–102.

    Google Scholar 

  • Krall, J. R., Mulholland, J. A., Russell, A. G., Balachandran, S., Winquist, A., Tolbert, P. E., et al. (2017). Associations between source-specific fine particulate matter and emergency department visits for respiratory disease in four US cities. Environmental Health Perspectives,125, 97.

    CAS  Google Scholar 

  • Lighty, J. S., Veranth, J. M., & Sarofim, A. F. (2000). Combustion aerosols: Factors governing their size and composition and implications to human health. Journal of the Air and Waste Management Association,50, 1565–1618.

    CAS  Google Scholar 

  • Maertens, R. M., White, P. A., Rickert, W., Levasseur, G., Douglas, G. R., Bellier, P. V., et al. (2009). The genotoxicity of mainstream and sidestream marijuana and tobacco smoke condensates. Chemical Research in Toxicology,22, 1406–1414.

    CAS  Google Scholar 

  • Maniya, K., & Bhatt, M. (2010). A selection of material using a novel type decision-making method: Preference selection index method. Materials and Design,31, 1785–1789.

    Google Scholar 

  • Maron, D. M., & Ames, B. N. (1983). Revised methods for the Salmonella mutagenicity test. Mutation Research/Environmental Mutagenesis and Related Subjects,113, 173–215.

    CAS  Google Scholar 

  • Mazzoli-Rocha, F., Fernandes, S., Einicker-Lamas, M., & Zin, W. A. (2010). Roles of oxidative stress in signaling and inflammation induced by particulate matter. Cell Biology and Toxicology,26, 481–498.

    CAS  Google Scholar 

  • McDonald, J. D., Eide, I., Seagrave, J., Zielinska, B., Whitney, K., Lawson, D. R., et al. (2004). Relationship between composition and toxicity of motor vehicle emission samples. Environmental Health Perspectives,112, 1527–1538.

    CAS  Google Scholar 

  • Miller, M. R., Shaw, C. A., & Langrish, J. P. (2012). From particles to patients; oxidative stress and the cardiovascular effects of air pollution. Future Cardiology,8, 577–602.

    CAS  Google Scholar 

  • Monn, C., & Becker, S. (1999). Cytotoxicity and induction of proinflammatory cytokines from human monocytes exposed to fine (PM2.5) and coarse particles (PM10–2.5) in outdoor and indoor air. Toxicology and Applied Pharmacology,155, 245–252.

    CAS  Google Scholar 

  • Nardo, M., Saisana, M., Saltelli, A., Tarantola, S., Hoffman, A., & Giovannini, E. (2005). Handbook on constructing composite indicators: Methodology and user guide. Paris: OECD publishing.

    Google Scholar 

  • Rohr, A. C., & Wyzga, R. E. (2012). Attributing health effects to individual particulate matter constituents. Atmospheric Environment,62, 130–152.

    CAS  Google Scholar 

  • Rutter, A. P., Snyder, D. C., Schauer, J. J., DeMinter, J., & Shelton, B. (2009). Sensitivity and bias of molecular marker-based aerosol source apportionment models to small contributions of coal combustion soot. Environmental Science and Technology,43, 7770–7777.

    CAS  Google Scholar 

  • Sam, K., Coulon, F., & Prpich, G. (2017). A multi-attribute methodology for the prioritisation of oil contaminated sites in the Niger Delta. Science of the Total Environment,579, 1323–1332.

    CAS  Google Scholar 

  • Sarnat, J. A., Marmur, A., Klein, M., Kim, E., Russell, A. G., Sarnat, S. E., et al. (2008). Fine particle sources and cardiorespiratory morbidity: An application of chemical mass balance and factor analytical source-apportionment methods. Environmental Health Perspectives,116, 459.

    Google Scholar 

  • Schwarze, P. E., Totlandsdal, A. I., Låg, M., Refsnes, M., Holme, J. A., Øvrevik, J. (2013). Inflammation-related effects of diesel engine exhaust particles: Studies on lung cells in vitro. BioMed Research International, 2013 , 1–13.

    Google Scholar 

  • Steenhof, M., Gosens, I., Strak, M., Godri, K. J., Hoek, G., Cassee, F. R., et al. (2011). In vitro toxicity of particulate matter (PM) collected at different sites in the Netherlands is associated with PM composition, size fraction and oxidative potential-the RAPTES project. Particle and Fibre Toxicology,8, 26.

    CAS  Google Scholar 

  • Straif, K., Cohen, A., & Samet, J. (2013). Air pollution and cancer. IARC Scientific Publication 161.

  • Tal, T. L., Simmons, S. O., Silbajoris, R., Dailey, L., Cho, S.-H., Ramabhadran, R., et al. (2010). Differential transcriptional regulation of IL-8 expression by human airway epithelial cells exposed to diesel exhaust particles. Toxicology and Applied Pharmacology,243, 46–54.

    CAS  Google Scholar 

  • Tecer, L. H., Alagha, O., Karaca, F., Tuncel, G., & Eldes, N. (2008). Particulate matter (PM2.5, PM10-2.5, and PM10) and children’s hospital admissions for asthma and respiratory diseases: A bidirectional case-crossover study. Journal of Toxicology and Environmental Health, Part A,71, 512–520.

    CAS  Google Scholar 

  • Totlandsdal, A. I., Låg, M., Lilleaas, E., Cassee, F., & Schwarze, P. (2015). Differential proinflammatory responses induced by diesel exhaust particles with contrasting PAH and metal content. Environmental Toxicology,30, 188–196.

    CAS  Google Scholar 

  • Valavanidis, A., Vlachogianni, T., Fiotakis, K., & Loridas, S. (2013). Pulmonary oxidative stress, inflammation and cancer: Respirable particulate matter, fibrous dusts and ozone as major causes of lung carcinogenesis through reactive oxygen species mechanisms. International Journal of Environmental Research and Public Health,10, 3886–3907.

    Google Scholar 

  • Vattanasit, U., Navasumrit, P., Khadka, M. B., Kanitwithayanun, J., Promvijit, J., Autrup, H., et al. (2014). Oxidative DNA damage and inflammatory responses in cultured human cells and in humans exposed to traffic-related particles. International Journal of Hygiene and Environmental Health,217, 23–33.

    CAS  Google Scholar 

  • Wang, J.-J., Jing, Y.-Y., Zhang, C.-F., & Zhao, J.-H. (2009). Review on multi-criteria decision analysis aid in sustainable energy decision-making. Renewable and Sustainable Energy Reviews,13, 2263–2278.

    Google Scholar 

  • Wang, Y.-M., & Luo, Y. (2010). Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making. Mathematical and Computer Modelling,51, 1–12.

    Google Scholar 

  • Yang, L., Liu, G., Lin, Z., Wang, Y., He, H., Liu, T., et al. (2016). Pro-inflammatory response and oxidative stress induced by specific components in ambient particulate matter in human bronchial epithelial cells. Environmental Toxicology,31, 923–936.

    CAS  Google Scholar 

  • Zheng, M., Wang, F., Hagler, G., Hou, X., Bergin, M., Cheng, Y., et al. (2011). Sources of excess urban carbonaceous aerosol in the Pearl River Delta Region. China Atmospheric Environment,45, 1175–1182.

    CAS  Google Scholar 

Download references

Acknowledgements

This research was supported by the National Research Foundation (NRF) of Korea (2014M3C8A5030618).

Author information

Authors and Affiliations

  1. School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, 123 Cheomdangwagi-ro, Buk-gu, Gwangju, 61005, Republic of Korea

    Injeong Kim, Kihong Park, KwangYul Lee, Minhan Park & Sang Don Kim

  2. Center for Chemicals Risk Assessment, Gwangju Institute of Science and Technology, 123 Cheomdangwagi-ro, Buk-gu, Gwangju, 61005, Republic of Korea

    Injeong Kim & Sang Don Kim

  3. Department of Industrial Plant Science and Technology, Chungbuk National University, Cheongju, Republic of Korea

    Heungbin Lim

  4. R&D Headquarter, KT&G, Daejeon, Republic of Korea

    Hanjae Shin

Authors
  1. Injeong Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kihong Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. KwangYul Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Minhan Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Heungbin Lim
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hanjae Shin
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Sang Don Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sang Don Kim.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

See Tables 5, 6, 7 and 8 and Figs. 3 and 4.

Table 5 Correlation between the cytotoxicities used in the decision-making matrix
Full size table
Table 6 Integrative toxicity score (ITS) and ranking of PM2.5 sources by weighting method
Full size table
Table 7 Global sensitivity analysis for the ranking orders by weighting method
Full size table
Table 8 Normalized decision-making matrix, indicator weight and integrative toxicity score (ITS) for ambient particulate matter of three sizes in the eight sites of the Netherlands (raw data of in vitro toxicity is reported by Steenhof et al. 2011)
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, I., Park, K., Lee, K. et al. Application of various cytotoxic endpoints for the toxicity prioritization of fine dust (PM2.5) sources using a multi-criteria decision-making approach. Environ Geochem Health 42, 1775–1788 (2020). https://doi.org/10.1007/s10653-019-00469-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10653-019-00469-2

Keywords

Search

Navigation